\begin{table}[!ht]
\caption{Evaluating whether political socialization confounds estimates of the relationship between education and participation}
\label{} 
\begin{tabular}{ l D{.}{.}{3}D{.}{.}{3}D{.}{.}{3}D{.}{.}{3}D{.}{.}{3} } 
\hline 
  & \multicolumn{ 1 }{ c }{ DV=Sup. UPRONA } & \multicolumn{ 1 }{ c }{ DV=Sup. FRODEBU } & \multicolumn{ 1 }{ c }{ DV=Sup. none } & \multicolumn{ 1 }{ c }{ DV=Sup. other } & \multicolumn{ 1 }{ c }{ DV=Rebel } \\ \hline
 %                        & DV=Sup. UPRONA    & DV=Sup. FRODEBU   & DV=Sup. none      & DV=Sup. other     & DV=Rebel         \\ 
(Constant)               & 0.158 ^*          & 0.640 ^{***}      & 0.180             & 0.002             & 0.029            \\ 
                         & (0.072)           & (0.097)           & (0.130)           & (0.008)           & (0.020)          \\ 
Age in 1972              & 0.016 ^{**}       & 0.030 ^{***}      & -0.047 ^{***}     & 0.001             & -0.001 ^*        \\ 
                         & (0.005)           & (0.006)           & (0.007)           & (0.001)           & (0.001)          \\ 
Age in 1972 sq.          & -0.001 ^*         & -0.002 ^{**}      & 0.002 ^{***}      & -0.000            & 0.000 ^\dagger  \\ 
                         & (0.000)           & (0.001)           & (0.001)           & (0.000)           & (0.000)          \\ 
Subj. ed.                & -0.004            & -0.019 ^\dagger  & 0.020 ^\dagger   & 0.001             & 0.003 ^{***}     \\ 
                         & (0.006)           & (0.011)           & (0.011)           & (0.001)           & (0.001)          \\ 
Father's ed.             & 0.011             & -0.013            & 0.004             & -0.001            & 0.003 ^*         \\ 
                         & (0.013)           & (0.009)           & (0.013)           & (0.002)           & (0.001)          \\ 
1993 support for FRODEBU &                   &                   &                   &                   & 0.020 ^{***}     \\ 
                         &                   &                   &                   &                   & (0.004)          \\ 
1993 support for none    &                   &                   &                   &                   & 0.008            \\ 
                         &                   &                   &                   &                   & (0.006)          \\ 
1993 support for other   &                   &                   &                   &                   & 0.126 ^\dagger  \\ 
                         &                   &                   &                   &                   & (0.071)           \\
 $N$                      & 905               & 905               & 905               & 905               & 905              \\ 
$R^2$                    & 0.135             & 0.174             & 0.315             & 0.045             & 0.034            \\ 
adj. $R^2$               & 0.113             & 0.152             & 0.297             & 0.020             & 0.006            \\ 
Resid. sd                & 10.309            & 13.585            & 12.542            & 2.723             & 4.240             \\ \hline
 \multicolumn{6}{l}{\footnotesize{Weighted least squares estimates.}}\\
\multicolumn{6}{l}{\footnotesize{Standard errors account for clustering at the commune level.}}\\
\multicolumn{6}{l}{\footnotesize{(Number of clusters is 65.)}}\\
\multicolumn{6}{l}{\footnotesize{All models control for pre-war province fixed effects and survival probability.}}\\
\multicolumn{6}{l}{\footnotesize{In results columns 1, 2, and 3, subj. ed. and father's ed. are jointly significant with p < .05.}}\\
\multicolumn{6}{l}{\footnotesize{$^\dagger$ significant at $p<.10$; $^* p<.05$; $^{**} p<.01$; $^{***} p<.001$}} 
\end{tabular} 
 \end{table}
Analysis of Variance Table

Model 1: support93_uprona ~ age1972 + I(age1972^2) + dm11 + dm12 + logitsurv + 
    as.factor(adm1npre)
Model 2: support93_uprona ~ age1972 + I(age1972^2) + logitsurv + as.factor(adm1npre)
  Res.Df   RSS Df Sum of Sq      F  Pr(>F)  
1    881 93634                              
2    883 94332 -2   -697.87 3.2831 0.03797 *
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Analysis of Variance Table

Model 1: support93_frodebu ~ age1972 + I(age1972^2) + dm11 + dm12 + logitsurv + 
    as.factor(adm1npre)
Model 2: support93_frodebu ~ age1972 + I(age1972^2) + logitsurv + as.factor(adm1npre)
  Res.Df    RSS Df Sum of Sq      F   Pr(>F)    
1    881 162599                                 
2    883 166625 -2   -4026.6 10.909 2.09e-05 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Analysis of Variance Table

Model 1: support93_none ~ age1972 + I(age1972^2) + dm11 + dm12 + logitsurv + 
    as.factor(adm1npre)
Model 2: support93_none ~ age1972 + I(age1972^2) + logitsurv + as.factor(adm1npre)
  Res.Df    RSS Df Sum of Sq      F    Pr(>F)    
1    881 138584                                  
2    883 141823 -2   -3239.1 10.296 3.802e-05 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Analysis of Variance Table

Model 1: support93_other ~ age1972 + I(age1972^2) + dm11 + dm12 + logitsurv + 
    as.factor(adm1npre)
Model 2: support93_other ~ age1972 + I(age1972^2) + logitsurv + as.factor(adm1npre)
  Res.Df    RSS Df Sum of Sq      F Pr(>F)
1    881 6532.9                           
2    883 6554.5 -2   -21.596 1.4562 0.2337
